Automated Classification of Severity of Age-Related Macular Degeneration from Fundus Photographs

Srihari Kankanahalli, Philippe M. Burlina, Yulia Wolfson, David E. Freund, Neil M. Bressler
<span title="2013-03-11">2013</span> <i title="Association for Research in Vision and Ophthalmology (ARVO)"> <a target="_blank" rel="noopener" href="" style="color: black;">Investigative Ophthalmology and Visual Science</a> </i> &nbsp;
PURPOSE. To evaluate an automated analysis of retinal fundus photographs to detect and classify severity of age-related macular degeneration compared with grading by the Age-Related Eye Disease Study (AREDS) protocol. METHODS. Following approval by the Johns Hopkins University School of Medicine's Institution Review Board, digitized images (downloaded at of field 2 (macular) fundus photographs from AREDS obtained over a 12year longitudinal study were classified
more &raquo; ... automatically using a visual words method to compare with severity by expert graders. RESULTS. Sensitivities and specificities, respectively, of automated imaging, when compared with expert fundus grading of 468 patients and 2145 fundus images are: 98.6% and 96.3% when classifying categories 1 and 2 versus categories 3 and 4; 96.1% and 96.1% when classifying categories 1 and 2 versus category 3; 98.6% and 95.7% when classifying category 1 versus category 3; and 96.0% and 94.7% when classifying category 1 versus categories 3 and 4; CONCLUSIONS. Development of an automated analysis for classification of age-related macular degeneration from digitized fundus photographs has high sensitivity and specificity when compared with expert graders and may have a role in screening or monitoring. (Invest Ophthalmol Vis Sci.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1167/iovs.12-10928</a> <a target="_blank" rel="external noopener" href="">pmid:23361512</a> <a target="_blank" rel="external noopener" href="">fatcat:mrqnv4twjrak5htccf4z5qpn3i</a> </span>
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